4 citations · 6 across the 14 of their papers we have counts for
6 papers · 1 filter
Enhancing LLM-Based Data Annotation with Error Decomposition
Zhen Xu, Vedant Khatri, Yijun Dai +4
Large language models offer a scalable alternative to human coding for data annotation tasks, enabling the scale-up of research across data-intensive domains. While LLMs are alread…
Memorization Dynamics in Knowledge Distillation for Language Models
Jaydeep Borkar, Karan Chadha, Niloofar Mireshghallah +6
Knowledge Distillation (KD) is increasingly adopted to transfer capabilities from large language models to smaller ones, offering significant improvements in efficiency and utility…
When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework
Zhen Xu, Shang Zhu, Jue Wang +5
We investigate the challenge of applying Large Language Models (LLMs) to long texts. We propose a theoretical framework that distinguishes the failure modes of long context tasks i…
Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models
Xumeng Wen, Shun Zheng, Zhen Xu +2
Recent studies have shown that large language models (LLMs), when customized with post-training on tabular data, can acquire general tabular in-context learning (TabICL) capabiliti…
Usefulness of LLMs as an Author Checklist Assistant for Scientific Papers: NeurIPS'24 Experiment
Alexander Goldberg, Ihsan Ullah, Thanh Gia Hieu Khuong +4
Large language models (LLMs) represent a promising, but controversial, tool in aiding scientific peer review. This study evaluates the usefulness of LLMs in a conference setting as…
Comprehensive Implementation of TextCNN for Enhanced Collaboration between Natural Language Processing and System Recommendation
Xiaonan Xu, Zheng Xu, Zhipeng Ling +2
Natural Language Processing (NLP) is an important branch of artificial intelligence that studies how to enable computers to understand, process, and generate human language. Text c…